Research Scientist, Google DeepMind

Research

Broadly speaking, I am interested in the algorithmic and
computational aspects of Artificial Intelligence, with a
particular emphasis on scalable and efficient approaches for online
Reinforcement Learning agents.

Reinforcement Learning / Universal AI

Consider an agent let loose in an unknown world with only a crude
reward signal and limited sensor information as feedback. An agent that
can be expected to accumulate a lot of reward in many different
worlds can be viewed as being generally intelligent. How might
we go about designing such an agent?